Evolution of a Robust Obstacle-avoidance Behavior in Khepera: a Comparison of Incremental and Direct Strategies
نویسنده
چکیده
An incremental approach is used to simulate the evolution of neural controllers for robust obstacle-avoidance in a Khepera robot and proves to be more eecient than a direct approach. During a rst evolutionary stage, obstacle-avoidance controllers in medium-light conditions are generated. During a second evolutionary stage, controllers avoiding strongly-lighted regions, where the previously acquired obstacle-avoidance capacities would be impaired, are obtained. The best controllers thus evolved are successfully downloaded on a Khepera robot. The SGOCE paradigm that is used in these experiments is described in the text. Future research will target at furthering the incremental evolutionary process and evolving more intricate behaviors.
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